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--- research_notes [2018/02/08 06:55] – [Research Notes & Project & Ideas] potthast
+++ research_notes [2023/03/28 09:14] (current) – external edit 127.0.0.1
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 [ [[research_notes_2016| Research Notes 2015/16]] ]
-====== Research Notes & Project & Ideas ======
+====== Research Notes & Project & Ideas 2018 ======
-The following lists contains active research questions in my personal research and that
+The following lists contains some active research questions in my personal research and that
-of my group members.
+of my group members in which I am directly involved.
-<box 80% round left #ffffff #ffffff #ffffff #000000|**Research Levels**>
+Model Reconstruction in a Large-Scale Environment [with Babatunde Odunuga]
-\\
-The projects range from **applied** research to **pure** research. I believe that it is important to
+Data Assimilation for Neural Fields [with Jehan Alswailhi]
-have <hi lightblue>all levels of research</hi> active in a society and it is my key interest to link them, to use
-very pure research in applications and to let applications inspire very basic questions and
+Ultra Rapid Data Assimilation, basic theory [with Christian Welzbacher]
-research topics.
-\\
-For this very reason I have not separated the projects into pure or applied - though the communities active
+Object Data Assimilation [with Christian Welzbacher und Uli Blahak]
-in the different areas and their style to write, to argue and to publish are quite different.
-</box>
+Particle Filter for NWP [with Anne Walter]
+Radar Radial Winds Error Correlations [Joanne Waller, Elisabeth Bauernschubert]
-\\
-==== A ====
+Survey about Global DA Systems [many authors]
+Bias Splitting [with Jason Otkin]
+Nonlinear Bias Correction for KENDA [with Jason Otkin]
-  * Multiscale Data Assimilation - with Aamir Nadeem **[PHD Project]**
-  * Model Approximations and Model Diagnostics in Data Assimilation Cycles - with Babatunde Odunuga **[PHD Project]**
+Shallow Water Model Particle Filter with Real Data [with Oana Lang, Dan Crisan and PJ van Leeuwen]
+GNSS DA [with Michael Bender]
+ICON DA Survey [with Ana Fernandez and many authors]
-  * Mathematical Analysis of Multistep Data Assimilation - with Perianez, Reich, Schraff, Rhodin
-  * <color blue>**Assimilating Satellite Cloud Product in an Ensemble Data Assimilation for NWP - with Schomburg and Schraff**</color>
+ Satellite DA for Regional Models [with Frederick Kurzrock and many authors]
+ Data Assimilation for ICON ART [with Vanessa Bachmann]
+BACY Introduction Paper [with Thomas Roesch, Harald Anlauf, ...]
-  * <hi>Orthogonality Sampling/ Direct Sampling and inverting the Volume Bessel Potential - RP</hi>
-{{no7original.jpg?200}}{{no7reconstruction.jpg?200}}{{z_no4_20150728t152030reconstruction.jpg?200}}\\
+SEVIRI VIS Assimilation [Lilo Bach, Christoph Schraff, ...]
-<sup>Original and reconstruction by direct sampling with volume Bessel potential inversion
-from a far field pattern of uniform sources
+Lightning Data Assimilation [Lisa Neef, Uli Blahak, ...]
-located in the rectangle, here using 7 different frequencies (left), using four frequencies between
-wavenumber 1.5 and 2.5, one incident field only (right). This is work in progress. </sup>
+Assimilation of Inequalities [with Elisabeth Bauernschubert]
-==== B ====
-  * <color brown>**GPS Slant Delay Operator - with Michael Bender et al.**</color>
+Projection Algorithms for ICON DA
-  * GPS Tomography Algorithms - with Michael Bender et al
-  * <color red>**Particle Filter for Large Scale Problems in NWP - with Schraff, Rhodin, Reich**</color>
-  * <color blue>**SEVIRI infrared radiance assimilation for convective models - with Otkin, Perianez et al.**</color>
-  * Mathematical Analysis for Ensemble Kalman Filter Convergence Questions - with Perianez et al. **[PHD Project - completed]**
-==== C ====
-  * Data Assimilation in Neural Field and Neural Mass Models - with Ingo Bojak
-  * <color blue>**Radar data assimilation in convective models - with Theresa Bick et al.**</color>
-{{fss_exp2_cycle_dbz.png?200}}{{fss_exp3_conv_lhn_radconv.png?200}}\\
-<sup>Radar Data Assimilation based on an Ensemble Kalman Filter in a Convection Permitting Model with Rapid Update Cycle. We show the influence on the cycling frequency on the fractional skill score. Here, for the 4d-Version of the LETKF, lower update rates lead to better fractional skill skores after one hour of forecast.(left) Further, we compare latent heat nudging with full Volume Radar assimilation (right) - they were of comparable quality in these experiments. The experiments have been carried out by Bick et al.</sup>
-  * <color blue>**Kilometer Scale Ensemble Data Assimilation (KENDA) - with Schraff, Reich, Rhodin et al. **</color> [under review]
-  * Diagnostics for Ensemble Data Assimilation Systems - with Dora Föhring, Rhodin and Köpken-Watts
-  * Wind Power Assimilation OSSE - with Stefan Declair, Annika Schomburg et al.
-==== D ====
-  * <color blue>Ensemble Data Assimilation for the ICON Model (IEDA) - with Ana Fernandez et al. </color>
-  * Inverse Problems for Delay Neural Field Equations - with Jehan Alswailhi **[PHD project]**
-  * Ensemble Methods for Inverse Scattering Problems - with Quaz Muhammad Zaigham Zia
-  * Photovoltaic Measurement Assimilation for Energy Applications - with Annika Schomburg et al.
-  * <hi>Data Assimilation for Cognitive Structures</hi> - RP
-{{nested_fprill_01.png?300}}\\
-<sup>ICON Global data assimilation model grid with NEST over Europe.</sup>